Biology and Management of Soybean Charcoal Rot

In the 2003 growing season, charcoal rot, a disease new to Iowa producers, was prevalent in the soybean fields of Iowa. This was the first ever statewide occurrence in Iowa with severe damage to many soybean fields. In the south, this disease has been a yield robber and has drastically reduced the yield potential by as mush as the sudden death syndrome. This article will discuss the following aspects of this disease: l) the distribution and economic importance of the pathogen; 2) identification of the disease; 3) the disease cycle and epidemiology; 4) yield loss assessment and 5) management strategies

Toward an internal gravity wave spectrum in global ocean models

Office of Naval Research, National Science FoundationPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/111824/1/grl_internalwavespectrum_2015.pd

Non-linear regression models for Approximate Bayesian Computation

Approximate Bayesian inference on the basis of summary statistics is well-suited to complex problems for which the likelihood is either mathematically or computationally intractable. However the methods that use rejection suffer from the curse of dimensionality when the number of summary statistics is increased. Here we propose a machine-learning approach to the estimation of the posterior density by introducing two innovations. The new method fits a nonlinear conditional heteroscedastic regression of the parameter on the summary statistics, and then adaptively improves estimation using importance sampling. The new algorithm is compared to the state-of-the-art approximate Bayesian methods, and achieves considerable reduction of the computational burden in two examples of inference in statistical genetics and in a queueing model.Comment: 4 figures; version 3 minor changes; to appear in Statistics and Computin

Transmission and Pathogenesis of Swine-Origin 2009 A(H1N1) Influenza Viruses in Ferrets and Mice

available in PMC 2010 October 12Recent reports of mild to severe influenza-like illness in humans caused by a novel swine-origin 2009 A(H1N1) influenza virus underscore the need to better understand the pathogenesis and transmission of these viruses in mammals. In this study, selected 2009 A(H1N1) influenza isolates were assessed for their ability to cause disease in mice and ferrets and compared with a contemporary seasonal H1N1 virus for their ability to transmit to naïve ferrets through respiratory droplets. In contrast to seasonal influenza H1N1 virus, 2009 A(H1N1) influenza viruses caused increased morbidity, replicated to higher titers in lung tissue, and were recovered from the intestinal tract of intranasally inoculated ferrets. The 2009 A(H1N1) influenza viruses exhibited less efficient respiratory droplet transmission in ferrets in comparison with the highly transmissible phenotype of a seasonal H1N1 virus. Transmission of the 2009 A(H1N1) influenza viruses was further corroborated by characterizing the binding specificity of the viral hemagglutinin to the sialylated glycan receptors (in the human host) by use of dose-dependent direct receptor-binding and human lung tissue–binding assays

AWclust: point-and-click software for non-parametric population structure analysis

<p>Abstract</p> <p>Background</p> <p>Population structure analysis is important to genetic association studies and evolutionary investigations. Parametric approaches, e.g. STRUCTURE and L-POP, usually assume Hardy-Weinberg equilibrium (HWE) and linkage equilibrium among loci in sample population individuals. However, the assumptions may not hold and allele frequency estimation may not be accurate in some data sets. The improved version of STRUCTURE (version 2.1) can incorporate linkage information among loci but is still sensitive to high background linkage disequilibrium. Nowadays, large-scale single nucleotide polymorphisms (SNPs) are becoming popular in genetic studies. Therefore, it is imperative to have software that makes full use of these genetic data to generate inference even when model assumptions do not hold or allele frequency estimation suffers from high variation.</p> <p>Results</p> <p>We have developed point-and-click software for non-parametric population structure analysis distributed as an R package. The software takes advantage of the large number of SNPs available to categorize individuals into ethnically similar clusters and it does not require assumptions about population models. Nor does it estimate allele frequencies. Moreover, this software can also infer the optimal number of populations.</p> <p>Conclusion</p> <p>Our software tool employs non-parametric approaches to assign individuals to clusters using SNPs. It provides efficient computation and an intuitive way for researchers to explore ethnic relationships among individuals. It can be complementary to parametric approaches in population structure analysis.</p

Identifying Signatures of Natural Selection in Tibetan and Andean Populations Using Dense Genome Scan Data

High-altitude hypoxia (reduced inspired oxygen tension due to decreased barometric pressure) exerts severe physiological stress on the human body. Two high-altitude regions where humans have lived for millennia are the Andean Altiplano and the Tibetan Plateau. Populations living in these regions exhibit unique circulatory, respiratory, and hematological adaptations to life at high altitude. Although these responses have been well characterized physiologically, their underlying genetic basis remains unknown. We performed a genome scan to identify genes showing evidence of adaptation to hypoxia. We looked across each chromosome to identify genomic regions with previously unknown function with respect to altitude phenotypes. In addition, groups of genes functioning in oxygen metabolism and sensing were examined to test the hypothesis that particular pathways have been involved in genetic adaptation to altitude. Applying four population genetic statistics commonly used for detecting signatures of natural selection, we identified selection-nominated candidate genes and gene regions in these two populations (Andeans and Tibetans) separately. The Tibetan and Andean patterns of genetic adaptation are largely distinct from one another, with both populations showing evidence of positive natural selection in different genes or gene regions. Interestingly, one gene previously known to be important in cellular oxygen sensing, EGLN1 (also known as PHD2), shows evidence of positive selection in both Tibetans and Andeans. However, the pattern of variation for this gene differs between the two populations. Our results indicate that several key HIF-regulatory and targeted genes are responsible for adaptation to high altitude in Andeans and Tibetans, and several different chromosomal regions are implicated in the putative response to selection. These data suggest a genetic role in high-altitude adaption and provide a basis for future genotype/phenotype association studies necessary to confirm the role of selection-nominated candidate genes and gene regions in adaptation to altitude

An Integrated TCGA Pan-Cancer Clinical Data Resource to Drive High-Quality Survival Outcome Analytics

For a decade, The Cancer Genome Atlas (TCGA) program collected clinicopathologic annotation data along with multi-platform molecular profiles of more than 11,000 human tumors across 33 different cancer types. TCGA clinical data contain key features representing the democratized nature of the data collection process. To ensure proper use of this large clinical dataset associated with genomic features, we developed a standardized dataset named the TCGA Pan-Cancer Clinical Data Resource (TCGA-CDR), which includes four major clinical outcome endpoints. In addition to detailing major challenges and statistical limitations encountered during the effort of integrating the acquired clinical data, we present a summary that includes endpoint usage recommendations for each cancer type. These TCGA-CDR findings appear to be consistent with cancer genomics studies independent of the TCGA effort and provide opportunities for investigating cancer biology using clinical correlates at an unprecedented scale. Analysis of clinicopathologic annotations for over 11,000 cancer patients in the TCGA program leads to the generation of TCGA Clinical Data Resource, which provides recommendations of clinical outcome endpoint usage for 33 cancer types

Episodic Occurrence of Favourable Weather Constrains Recovery of a Cold Desert Shrubland After Fire

Key to the long-term resilience of dryland ecosystems is the recovery of foundation plant species following disturbance. In ecosystems with high interannual weather variability, understanding the influence of short-term environmental conditions on establishment of foundation species is essential for identifying vulnerable landscapes and developing restoration strategies. We asked how annual environmental conditions affect post-fire establishment of Artemisia tridentata, a shrub species that dominates landscapes across much of the western United States, and evaluated the influence of episodic establishment on population recovery. We collected A. tridentata stem samples from 33 plots in 12 prescribed fire sites that burned 8–11 years before sampling. We determined individual establishment years using annual growth rings. We measured seasonal soil environmental conditions at the study sites and asked if these conditions predicted annual establishment density. We then evaluated whether establishment patterns could be predicted by site-level climate or dominant subspecies. Finally, we tested the effect of the magnitude and frequency of post-fire establishment episodes on long-term population recovery. Annual post-fire recruitment of A. tridentata was driven by the episodic availability of spring soil moisture. Annual establishment was highest with wetter spring soils (relative influence [RI] = 19.4%) and later seasonal dry-down (RI = 11.8%) in the year of establishment. Establishment density declined greatly 4 to 5 years after fire (RI = 17.1%). Post-fire establishment patterns were poorly predicted by site-level mean climate (marginal R2 ≤ 0.18) and dominant subspecies (marginal R2 ≤ 0.43). Population recovery reflected the magnitude, but not the frequency, of early post-fire establishment pulses. Post-fire A. tridentata density and cover (measured 8–11 years after fire) were more strongly related to the magnitude of the largest establishment pulse than to establishment frequency, suggesting that population recovery may occur with a single favourable establishment year. Synthesis and applications. This study demonstrates the importance of episodic periods of favourable weather for long-term plant population recovery following disturbance. Management strategies that increase opportunities for seed availability to coincide with favourable weather conditions, such as retaining unburned patches or repeated seeding treatments, can improve restoration outcomes in high-priority areas